In general terms, the optimum approach for interpreting well log data obtained by dipmeter is visual inspection and correlation by a skilled and experienced operator. The dipmeter analyst utilizes an optical device to shift and contrast two or more curves obtained from a dipmeter. Attempts to accomplish this by something other than human observation have been made in the past. Another approach is correlation of dipmeter logs by fixed interval correlation methods. The various and sundry mechanized correlation methods impose on the data the requirements for data free of noise, or what otherwise is termed as high quality data. The quality of data sometimes will vary in a fashion that poor quality cannot be overcome. For instance, the quality of data is dependent on downhole conditions which vary with a multiple of factors. The conditions impact the quality of curves presented for dipmeter interpretation. When such difficulties arise, as a practical matter, the only approach then left is optical correlation. Again, optical correlation may be the most accurate and desirable approach but it is also a good deal more expensive and tedious in that it requires an experienced human operator.
The present approach is able t o provide interpretation in the stead of fixed interval correlation techniques. In general terms, the approach of the present disclosure utilizes what are called segmentation trees with hierarchial multilevel optimization. These terms will be defined in greater sweep below.
The use of the generally described concepts implemented in the present apparatus and procedure enhance showings of dip angle and direction. Because there is a hierarchy of data, dynamic programming techniques are more readily applied.